Mixed precision estimate instruction computing narrow precision result for wide precision inputs

ABSTRACT

A technique is provided for performing a mixed precision estimate. A processing circuit receives an input of a first precision having a wide precision value. The processing circuit computes an output in an output exponent range corresponding to a narrow precision value based on the input having the wide precision value.

BACKGROUND

The present invention relates to data processing, and more specifically,to mixed precision estimate instruction computing.

The IEEE Standard for Floating-Point Arithmetic (IEEE 754) is atechnical standard established by the Institute of Electrical andElectronics Engineers (IEEE) and the most widely used standard forfloating-point computation. The current version is IEEE Standard forFloating-Point Arithmetic 754-2008, which was published in August 2008,and is herein incorporated by reference in its entirety. Many computerlanguages allow or require that some or all arithmetic be carried outusing IEEE 754 formats and operations.

The IEEE 754-2008 standard defines: arithmetic formats: sets of binaryand decimal floating-point data, which consist of finite numbers(including signed zeros and subnormal numbers), infinities, and special“not a number” values (NaNs); interchange formats: encodings (bitstrings) that may be used to exchange floating-point data in anefficient and compact form; rounding algorithms: methods to be used forrounding numbers during arithmetic and conversions; operations:arithmetic and other operations on arithmetic formats; and exceptionhandling: indications of exceptional conditions (such as division byzero, overflow, etc.).

Under exception handling, the standard defines five exceptions, each ofwhich has a corresponding status flag that is raised when the exceptionoccurs. The five possible exceptions are: invalid operation (e.g.,square root of a negative number); division by zero; overflow (a resultis too large to be represented correctly); underflow (a result is verysmall (outside the normal range) and is inexact); and inexact.

Single precision floating point format is a computer number format thatoccupies 4 bytes (32 bits) in computer memory and represents a widedynamic range of values by using a floating point. In IEEE 754-2008, the32-bit base 2 format is officially referred to as binary32.

In computing, double precision floating point is a computer numberformat that occupies two adjacent storage locations in computer memory.A double precision number, sometimes simply called a double, may bedefined to be an integer, fixed point, or floating point (in which caseit is often referred to as FP64). Modern computers with 32-bit storagelocations use two memory locations to store a 64-bit double-precisionnumber (a single storage location can hold a single-precision number).Double-precision floating-point is an IEEE 754 standard for encodingbinary or decimal floating-point numbers in 64 bits (8 bytes).

SUMMARY

According to exemplary embodiments, a computer system, method, andcomputer program product are provided for performing a mixed precisionestimate. A processing circuit receives an input of a wide precisionhaving a wide precision value. The processing circuit computes an outputin an output exponent range corresponding to a narrow precision valuebased on the input having the wide precision value.

Additional features and advantages are realized through the techniquesof the present invention. Other embodiments and aspects of the inventionare described in detail herein and are considered a part of the claimedinvention. For a better understanding of the invention with theadvantages and the features, refer to the description and to thedrawings.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

The subject matter which is regarded as the invention is particularlypointed out and distinctly claimed in the claims at the conclusion ofthe specification. The forgoing and other features, and advantages ofthe invention are apparent from the following detailed description takenin conjunction with the accompanying drawings in which:

FIG. 1 illustrates a table showing IEEE 754-2008 standard number formatsfor floating point numbers;

FIG. 2 illustrates a block diagram of executing a computation for asingle precision input value to result in a single precision outputvalue;

FIG. 3 illustrates a block diagram of a computer system according to anembodiment of the present invention;

FIG. 4 is a block diagram in which a double precision reciprocalestimate processes a double precision input and returns a singleprecision result according to an embodiment of the present invention;

FIG. 5 illustrates a flow chart according to an embodiment of thepresent invention;

FIG. 6 illustrates a 32 bit register and a 64 bit register according toan embodiment of the present invention;

FIG. 7 illustrates a block diagram of how the circuits allow a mantissawith excess precision bits for results corresponding to single precisiondenormalized numbers according to an embodiment of the presentinvention;

FIG. 8 illustrates a block diagram that generates and applies a mantissamask to an output according to an embodiment of the present invention;

FIG. 9 illustrates a flow chart for computing the mantissa mask andapplying the mantissa mask to the computed reciprocal estimate accordingto an embodiment of the present invention;

FIG. 10 illustrates a method for reciprocal estimate (computation) withmixed precision according to an embodiment of the present invention;

FIG. 11 illustrates a block diagram of a double precision multiplyestimate function according to an embodiment of the present invention;

FIG. 12 illustrates an example of a computer having capabilities, whichmay be utilized in accordance with embodiments of the present invention;and

FIG. 13 illustrates an example of a computer program product on acomputer readable/usable medium according to an embodiment of thepresent invention.

DETAILED DESCRIPTION

Exemplary embodiments are configured to execute mixed precision estimateinstruction computing. In one implementation, a circuit can receive aninput in a double precision format, compute the estimate instruction,and provide an output as a single precision result. The single precisionresult can be stored in a register according to a single precisionformat.

IEEE floating point standard 754-2008 specifies support for mixedprecision arithmetic. However, support for mixed precision estimateinstructions implemented by common instruction sets but not specified bythe IEEE standard has not been proposed by those skilled in the art.

Estimate instructions, such as reciprocal estimate (such as, e.g., for1/x) and reciprocal square root estimate (such as, e.g., 1/√x) are notstandardized. They are frequently implemented in accordance withstandard instruction sets, such as Power ISA™ of IBM®. The publicationof Power ISA™ Version 2.06 Revision B, dated Jul. 23, 2010 is hereinincorporated by reference in its entirety. The state of the art has notoffered mixed precision processing. Mixed precision processing refers tohaving an input of one precision such as double precision (e.g., 64 bitprecision format) and output of a different precision such as singleprecision (e.g., 32 bit precision format).

In current implementations, double precision reciprocal estimateinstructions and reciprocal square root estimate give a result fordouble precision inputs. In Power ISA™, double precision reciprocal orsquare root estimate instructions give a result for single precisioninputs when a shared architected register file format is used.

In current implementations, single precision reciprocal estimateinstructions and single precision reciprocal square root estimateinstructions give a result for single precision inputs. No formatssupport processing of a mixed precision double to single precisionestimate, where a proper single precision result is provided. Asincorporated herein by reference, a proper or valid single precisionresult is defined in IEEE floating point standard 754-2008.

FIG. 1 is a table 100 showing IEEE 754-2008 standard number formats forfloating point numbers. Row 1 through row 7 shows the various types ofprecision that may be used in number format. For example, row 2 showsbinary 32 which require 32 bits of memory in a register to store avalue, and binary 32 is referred to as single precision. Row 3 showsbinary 64 which requires 64 bits of memory in a register to store avalue in the memory of register, and binary 64 is referred to as doubleprecision.

For explanation purposes, examples may discuss single precision (32bits) and double precision (64 bits) as the input value and/or outputvalue, but the disclosure is not meant to be limited.

In accordance with an exemplary embodiment, estimate instructions areprovided corresponding to a lower precision that take inputs of anotherhigher precision and range. A result is computed, and an estimate isreturned corresponding to a number in the lower precision in accordancewith the architecture.

FIG. 2 is a block diagram 200 of executing a computation for a singleprecision input value to result in a single precision output value.

The single precision input value 205 is input into a reciprocal estimatefunction 210, a ±zero detect 215, and a ±infinity (∞) detect 220. Amultiplexer 225 also referred to as a data selector receives input fromthe computed reciprocal estimate function 210, +zero, −zero, +infinity,and −infinity. The multiplexer 225 selects the desired input based onwhether the zero detect 215 detects a zero and/or whether the infinitydetect 220 detects infinity. If nothing is detected by the zerodetection 215 and the infinity detect 220, the multiplexer 225 passesthe computed value from the reciprocal estimate function 210, and thiscomputed value is a single precision result value 230. Further, logic ofthe multiplexer 225 is provided in Table 1 below. This logic applies forthe zero detect 215 and infinity detect 220 as will be discussed later.

TABLE 1 If (detect_plus_0) then  output <= plus_infinity; elseif(detect_minus_0) then  output <= minus_infinity; If(detect_plus_infinity) then  output <= plus_0; elseif(detect_minus_infinity) then  output <= minus_0; else  output <=estimate_circuit_result; end if;

If the reciprocal estimate function 210 calculates, e.g., 1/x or 1/√x,the single precision input value 205 is “x” or “x^(n)”. In this case, xis a 32 bit value in the 32 bit single precision format as defined byIEEE 754-2008, and the single precision result value 230 is in the sameformat. The input value may be retrieved from a register and the outputvalue may be stored in a register. In one embodiment, a single precisionestimate circuit may further have logic to handle the replication of aNaN input to a NaN output.

Turning now to FIG. 3, a block diagram of a system 300 is generallyshown according to an exemplary embodiment. The system 300 includes aprocessor 305 also referred to as a central processing unit (CPU). Theprocessor 305 has one or more processor cores, and the processor coremay be referred to as circuitry 310. The processor 305 may include oneor more registers 315. In computer architecture, a processor register isa small amount of storage available as part of a CPU or other digitalprocessor, and data can be loaded into the register 315 from memory 320for arithmetic manipulation by the circuitry 310.

Circuits 312 are part of the circuitry 310 of the processor 305. Thecircuits 312 are configured with logical circuits to perform the variousarithmetic operations as discussed herein, according to an exemplaryembodiment. Additionally, software application 314 is configured withlogic to perform the various arithmetic operations as discussed herein,according to an exemplary embodiment. As such, any discussion ofoperations executed by circuits 312 can also be performed by thesoftware application 314. The memory 320 may include program code 325 asan operating system for the system 300.

FIG. 4 is a block diagram 400 where a double precision reciprocalestimate processes a double precision input and returns a singleprecision result according to a first embodiment. In FIG. 4, estimateinstructions avoid rounding and denormalization circuits commonly usedfor arithmetic operations, which reduces cost and space when buildingprocessor circuits like the processor 305. In FIG. 4, the circuits 312are configured with the circuits to perform the operations, and thecircuits 312 store the output (the number/answer) in the register 315according to the desired precision format.

The circuits 312 are configured to retrieve a double precision inputvalue 405 from register 1 of registers 315 in a binary 64 bit format. Inone case, the circuits 312 are configured to perform/execute blocks 410,215, 220, 425 and 430 in parallel (i.e., concurrently) and/or nearlyparallel. The circuits 312 are configured to execute a double precisionreciprocal estimate function 410 (such as, e.g., 1/x or 1/x^(n))according to rules for 32 bit single precision format as defined by IEEE754-2008. The circuits 312 are configured to perform the ±zero detect215, and the ±infinity (∞) detect 220. Additionally, the circuits 312are configured to perform an exponent <−127 detect 425 and anexponent >127 detect 430, where the exponent <−127 detect 425 and theexponent >127 detect 430 define the normalized range. If the circuits312 detects that the double precision input value 405 has an exponent<−127 (which corresponds to a denormalized single precision number) forwhich the results of a reciprocal estimate cannot be represented as anormalized single precision number, the circuits 312 are configured toforce the single precision result value 450 to infinity (∞) via amultiplexer 435. If the circuits 312 determine that the double precisioninput value 405 has an exponent >127 in which the double precisionreciprocal estimate function 410 is to compute, the circuits 312 areconfigured to output zero as the single precision result value 450. Thecircuits 312 operate the zero detect 215 and infinity detect 220 asdiscussed above in Table 1.

If the detects 215, 220, 425, and 430 are empty, the multiplexer 435 ofthe circuits 312 are configured to output the calculation (by circuits312) of the double precision reciprocal estimate function 410 as thesingle precision result value 450. In at least one embodiment, areciprocal estimate function returns a limited number of mantissa bits,e.g., 8 or 12 bits.

While this embodiment is generally configured to avoid denormalizedresult numbers by substituting zero results, the embodiment describedherein is equipped to generate a limited range of denormalized resultscorresponding to denormalized results that may be generated in responseto the input of a valid single precision input. Consequently, in oneembodiment, there is provided a means to generate said limited range,e.g., by way of a limited form alignment shift that exists in thedataflow to handle generating denormalized estimates for an inputexponent equal to 127 (the largest single precision input) in the doubleprecision reciprocal estimate function 410 of the circuits 312. In suchan embodiment, the circuits 312 may be configured to handle 1 or 2 bitsof denormalization. In another embodiment, no support for handling anydenormalized numbers is present in circuit 410. In accordance with suchan embodiment, an exponent check 430 (of exp >127 detect 430) may bereplaced by an alternate exponent check 430 to check for “exp >126” or“exp >125” to avoid results in the denormalized single precision range.

In one exemplary embodiment, the circuits 312 are configured to performreciprocal estimate function with not a number processing (NaN)processing in accordance with single precision NaN processing rulesconfigured in the circuits 312.

FIG. 5 is a flow chart 500 that corresponds to the block diagram 400according to the first embodiment. The circuits 312 are configured tocalculate the reciprocal estimate for input of one precision (such as 64bit precision) to provide the output in a different precision (32 bitprecision in the single precision format defined IEEE 754-2008).

At block 505, the circuits 312 are configured to read the input value,which may be a 64 bit input value (which corresponds to wide precision).At block 510, the circuits 312 include one or more circuits configuredto check whether the input exponent (of the input value) is less thannegative 127 (i.e., exp <−127). In response to determining that theinput exponent is less than −127, the circuits 312 are configured to setthe result value to plus or minus infinity (±∞) at block 530, dependingon the sign of the input value. If block 510 is no, the circuits 312 areconfigured to check whether the input exponent is greater than 126(i.e., exp >126) at block 515. In response determining that the inputexponent is greater than 126, the circuits 312 are configured to set theresult value to plus or minus zero (±0) at block 525, depending on thesign of the input value. If block 515 is no, the circuits 312 areconfigured to compute the reciprocal estimate of the input value atblock 520. Computing the reciprocal estimate at block 520 can includethe description discussed for diagram 200 in FIG. 2.

At block 535, the circuits 312 are configured to write the result valuein a 32 bit format for single precision (in register 315) (according tothe IEEE format for 32 bits) even when the input value is provided in 64bit format. One skilled in the art will understand that the checks andsteps can be re-ordered in a number of ways while practicing theteachings contained herein.

In one implementation of the first embodiment, blocks 510, 515, and 520are executed in parallel (e.g., concurrently or almost concurrently) bythe circuits 312. By having blocks 510, 515, 525, and 530, no roundingcircuit and no normalization circuit are needed in the circuits 312.Also, the circuits 312 avoid the additional clock cycle(s) (of theprocessor 305) required for the rounding circuit, and avoid theadditional clock cycle(s) required for the normalization circuit.

The circuits 312 may be configured to be specific to instruction setsthat represent a narrow precision format (such as 32 bits) as overlaysonto a wider precision format of a register (of registers 315), as inthe Power® ISA of IBM®.

In one example, results in single precision are represented in a bitpattern corresponding to double precision in the register file (ofregisters 315) for processing. A number is architecturally a singleprecision number only if the stored exponent matches the singleprecision range, and if only bits of the mantissa (also referred to asthe fraction and significand) corresponding to bits in the architectedsingle precision format are non-zero.

For example, FIG. 6 illustrates a single precision number in a 32 bitregister 605 and a 64 bit register 610 for a double precision number.The circuits 312 are configured to store the single precision number(that would normally be stored in the 32 bit register 605) in the 64 bitregister 610. This can be done by converting the single precisionexponent to a double precision exponent and by ensuring that the loworder 29 mantissa bits (to the right) are zero as shown in the 64 bitregister 615. Accordingly, the single precision number isarchitecturally represented in the architected register file of the 64bit register 615 (of the registers 315) as a collection of bitscorresponding to double precision.

The circuits 312 are configured to store single precision denormalizednumbers in an internal format corresponding to double precision numbersin a register of the registers 315. The circuits 312 can store thesingle precision number as an unnormalized number with an exponentcorresponding to exponent =−127 (i.e., not an implicit 0 beforedecimal). Particularly, in one case, the circuits 312 can store theimplicit bit explicitly. Since the single precision number is beingstored in a 64 bit register, the circuits 312 are also configured tostore the single precision denormalized number as a normalized doubleprecision number in the 64 bit register.

According to a second embodiment as discussed in FIG. 7, when denormalsingle precision results are returned (after computing the reciprocalestimate), the denormal numbers are stored (by the circuits 312) in aregister file format (of the register 315) having wider precision (e.g.,64 bits), but the circuits 312 allow the mantissa (i.e., fraction) tohave excess precision bits (i.e., more than the mantissa bits for singleprecision as set forth in IEEE 754-2008) for results corresponding tosingle precision denormalized numbers, corresponding to less than 23bits for denormalized numbers depending on the effective exponent of thedenormalized single precision number (and less than the number of bitsreturned by 410). In computer science, denormal numbers or denormalizednumbers (often called subnormal numbers) fill the underflow gap aroundzero in floating point arithmetic: any non-zero number which is smallerthan the smallest normal number is ‘sub-normal’. For example, if thesmallest positive ‘normal’ number is 1×β^(−n) (where β is the base ofthe floating-point system, usually 2 or 10 and n is the exponent), thenany smaller positive numbers that can be represented are denormal.

In accordance with the present definition of computing a mixed precisionresult, in first embodiment, a result is generated in the internalformat that meets the exponent range requirements of a single precisionformat.

However, in the second embodiment, for a generated result, excessivemantissa bits that are non-zero are generated by the circuits 312. Inaccordance with a floating point unit including such an embodiment,instructions operating on “single precision” numbers are either (1)equipped to process such inputs and compute and round an accurate resultbased on the full mantissa width presented, (2) or equipped to round ortruncate such numbers prior to processing. In particular, an example of(1) may be an instruction handling mixed-mode arithmetic and processingthe input similar to a double precision mantissa, and an example of (2)may be the Power® ISA single precision floating point store.

Turning to FIG. 7, a block diagram 700 illustrates how the circuits 312allow a mantissa (i.e., fraction) with excess precision bits for resultscorresponding to single precision denormalized numbers according to thesecond embodiment.

The circuits 312 are configured to read the input value 405. Asdiscussed above, the circuits 312 are configured to execute the zerodetect 215, execute the infinity detect 220, execute the exponent lessthan negative 127 detect 425, and compute the double precisionreciprocal estimate function 410 in parallel; additionally (inparallel), the circuits 312 are configured to execute an input exponentgreater than 149 detect 705. In the first embodiment, the input exponentcould not be greater than 127, in which case the single precision resultvalue 450 would have been designated as zero in the register. However,in the second embodiment, the input exponent is checked and has to begreater than 149 before the circuits 312 designate the single precisionresult value 450 as zero (0).

In accordance with one aspect of a microprocessor and more specificallya floating point unit support an embodiment generating excessivemantissa bits associated with a result in single precision denormalizedresult are handled by a single precision instruction accepting doubleprecision inputs, with a result rounded or truncated to single precisionin accordance with the IEEE 754 standard and augmented by the teachingsherein. In another aspect, a result is truncated when it is provided asan input to a single precision instruction, e.g., in accordance with thePower ISA floating point single store instruction.

In one case of the second embodiment, only one number with inputexponent=149 (e.g., 1·2¹⁴⁹) can be represented with a non-zerodenormalized result value. The cut off may be performed accordingly atinput exponent >148.

In accordance with a third embodiment, denormal (i.e., denormalized)single precision results are returned, where the denormalized singleprecision results are represented (by the circuits 312) in anarchitected register file format (in a register of the registers 315)corresponding to a wider precision (such as a 64 bit format), and therange of both the exponent and the precision of mantissa bits arerestricted to numbers representable in a narrower format (such as a 32bit format). In the third embodiments, the circuits 312 are allowed todeviate from the exact storage format for 32 bit single precision. Notethat in FIG. 6, bit 0 through 22 are the 23 fraction/mantissa bits, bits23 through 30 are the 8 exponent bits, and bit 31 is the sign bit; thisformat is slightly modified for storing the single precision resultvalue in a 64 bit register, but the total amount of bits is still 32bits as seen below.

Single precision denormalized values are represented in double precisionnon-denormalized number format (which is a double precision normalizednumber format). For example, when single precision denormalized numbersare represented in an architected wide format (64 bit register), andde-normalized narrow format numbers are represented in a normalizedformat, then only a limited number of bits can correspond to the nativesingle precision format illustrated in the 32 bit register 605. Forexample, Table 2 provides bit accuracy for the input exponent of theinput value and how the circuits 312 restrict the bits of the mantissato account for input exponents from −128 to −149, which exceed thesingle precision format of mantissa bits. By using an extra exponent bitin the 64 bit register (which has 11 exponent bits available), thecircuits 312 store a denormalized single precision result in a 64 bitregister (of the registers 315) according to Table 2.

Bit accuracy in Table 2: Exp = −126 23 mantissa bits + 1 implicit bitExp = −127 23 mantissa bits + 1 implicit bit Exp = −128 22 mantissabits + 1 implicit bit Exp = −129 21 mantissa bits + 1 implicit bit . . .Exp = −149  1 mantissa bit + 1 implicit bit

In state of the art, the single precision denormalized number would havebeen generated to denorms and been subjected to a rounding step at apredefined position corresponding to 23 mantissa bits.

However, to avoid the need for the normalization and denormalizationalignment shift (i.e., to avoid utilizing a normalization circuit and adenormalization circuit in the circuitry 310 of the processor 305), amask is applied (by the circuits 312) to the mantissa. In accordancewith the third embodiment, the rounding and/or truncation (correspondingto a round towards zero) mask can be generated in parallel with thecomputation of the floating point result, and be based on the inputexponent.

Turning to FIG. 8, a block diagram 800 shows the third embodiment whichbuilds on the first and second embodiments. In the diagram 800, thecircuits 312 load the input value 405 from one of the (64 bit format)registers 315. Since the (same) circuits 312 are configured for mixedprecision inputs and outputs, the input value 405 can be a doubleprecision 64 bit number and/or a single precision 32 bit number. Assumethat in this case, the input value is a double precision number of aform such that after the computation the output would result in a singleprecision denormalized number (this would require a separate roundingcircuit and denormalization circuit in the state of the art system).

As discussed above for the input value 405, the circuits 312 areconfigured to execute the zero detect 215, execute the infinity detect220, execute the exponent less than negative 127 detect 425, execute aninput exponent greater than 149 detect 705, and compute the doubleprecision reciprocal estimate function 410 in parallel. Additionally (inparallel), the circuits 312 are configured to execute the maskgeneration 805 for the mantissa bits to be represented in a 32 bitformat. The fraction (i.e., mantissa) bits are limited to 23 bits asshown in the 32 bit register 605 in FIG. 6. However, the circuits 312(in the third embodiment) allow the input exponent to be greater than125 (up to 148) without a rounding circuit and/or denormalizationcircuit by utilizing the additional exponent bits (e.g., 1 exponent bit)that are available in the 64 bit register (of the registers 315). Notethat the single precision format (32 bits) only has 8 bits available forthe exponent, while a number stored in double precision format has 11exponent bits available as shown in FIG. 6. To represent the computedoutput (i.e., the answer computed by the double precision reciprocalestimate function 410) of a number with an input exponent greater 127but less than 149 that was the input value 405, the circuits 312 utilizean additional exponent bit from the 64 bit format because the resultsare stored in a 64 bit register of the registers 315. Unlike in anembodiment using a denomalized internal representation, the fullmantissa is available for storing non-zero mantissa bits which may leadto excess precision, in accordance with the second embodiment. Assumethat the double precision reciprocal estimate function 410 (e.g., thecomputation circuit of the circuits 312) has calculated a value that istoo large (or too small) to be represented in the 32 bit format in 32bit register 605 and does not violate the blocks 215, 220, 425, and 705.In accordance with the third embodiment, the circuits 312 apply themantissa mask to the mantissa of the output number of the doubleprecision reciprocal estimate function 410 during mantissa masking 810,while using an extra bit of the exponent bits (e.g., 9 exponent bitsinstead of 8 exponent bits). The output after mantissa masking 810results in the single precision result value 450. This single precisionresult value 450 is stored in the 64 bit register in a 32 bit registerformat by using mantissa masking 810.

In accordance with the mantissa masking feature disclosed herein, thenumber of non-zero mantissa bits of an internal double precisionrepresentation is reduced to the number of non-zero mantissa bitsavailable in a single precision denormalized number, when the doubleprecision representation represents this value as a normalized doubleprecision value. Thus, mantissa masking ensures generation of singleprecision results without excess mantissa bits.

In accordance with the third embodiment, FIG. 9 is a flow chart 900 ofthe circuits 312 computing the mantissa mask and applying the mantissamask to the computed reciprocal estimate, while using an extra exponentbit. As can be seen, the third embodiment builds on features discussedin the first and second embodiments.

The circuits 312 read the input value 505. The circuits 312 checkwhether the input exponent is less than −127 at block 510. When circuits312 determine that the input exponent is less than −127, the circuits312 set the result value to infinity at block 530, and write the resultvalue in the register 315 at block 535. When the circuits 312 determinethat the input exponent is not less that −127, the circuits 312 checkwhether the exponent of the input value is greater than 149 at block910. When circuits 312 determine that the input exponent is greater than149, the circuits 312 set the result value to 0 at block 525 and writethe result value in the register 315 at block 535. When the circuits 312determine that the input exponent is not greater than 149, the circuits312 compute the reciprocal estimate at block 520.

In a case when the input exponent is greater than 127 but less than 149and the result value needs to be in single precision format (i.e., 32bits), rounding would be required for the number (which is too large)computed by the compute reciprocal estimate at block 520. However, thecircuits 312 are configured to compute a mantissa mask based on theinput value at block 910. The circuits 312 apply the mantissa mask tothe mantissa (i.e., the fraction part) of the computed reciprocalestimate at block 915. The circuits 312 write the result value in the 64bit register of the registers 315 at block 535. Based on the particularinput exponent of the input value, the circuits 312 use, e.g., 9exponent bits to store the (large) result value and zeros thecorresponding amount bits in the mantissa. The circuits 312 may executeblocks 510, 905, 520, and 910 in parallel (i.e., concurrently or almostcurrently).

For each input value, there is a predefined number of mantissa bits thatare to have zeros (0s) to maintain a total of 32 bits, such that theresult value can be presented (from the storage in register) to the useror to a computer program according to the IEEE 754-2008 single precisionformat, even though 9 exponent bits are used to store the result valuein 64 bit register of the registers 315. Since only a total of 32 bitsare used, the circuits 312 convert the 9 exponent value back to an 8exponent value to be in accord with the 32 bit format as shown in FIG. 6when a 32 bit format must be presented.

An exemplary embodiment of conversion to convert a 9 bit exponent inaccordance with a double precision format to an 8 bit exponent is shownherein in Table 3, where WORD0:31 is the 32b single precision word andDWORD0:63 is the 64b input double precision double word:

TABLE 3 No Denormalization Required (includes Zero/Infinity/NaN) ifDWORD1:11 > 896 or DWORD1:63 = 0 then WORD0:1 <= DWORD0:1 WORD2:31 <=DWORD5:34 Denormalization Required if 874 ≦DWORD1:11 ≦896 then sign <=DWORD0 exp <= DWORD1:11 − 1023 frac0:52 <= 0b1 ∥ DWORD12:63 denormalizeoperand do while exp < −126 frac0:52 <= 0b0 ∥ frac0:51 exp <= exp + 1WORD0 <= sign WORD1:8 <= 0x00 WORD9:31 <= frac1:23 else WORD <=undefined

Table 4 shows an example of the mantissa mask logic to be applied to themantissa bits (52 mantissa bits) allocated in the 64 bit register, whenthe result value is being written according to single precision.

TABLE 4 Mantissa mask logic: For i = 0 to 52    Mantissa_out(i) <=mantissa_in(i) AND    mantissa_mask(i) End for

For each bit position in the 53 bit mantissa, the input bit ofmantissa_in of a position is ANDed with a corresponding bit positionmask bit, to yield an output mantissa bit for that bit position. Oneskilled in the art would understand how to adapt bit masking toscenarios with mantissas of different widths according to the teachingsherein.

In order to avoid the delay of computing a mask from the outputexponent, when the output exponent has been determined, the outputmantissa mask is computed from the input exponent (by the circuits 312)as shown in Table 5 to be applied to a normalized register filerepresentation in a wider double precision format corresponding to adenormalized architected single precision result.

TABLE 5 Exp <= 125 23 mantissa b + 1 implicit b Exp = 126 22 mantissab + 1 implicit b Exp = 127 21 mantissa b + 1 implicit b Exp = 128 20mantissa b + 1 implicit b . . . Exp = 148  0 mantissa b + 1 mantissa b

As can been seen in Table 5, as the input exponent increases thecircuits 312 correspondingly reduce the bits utilized in the mantissabecause the circuits 312 use an extra exponent bit (i.e., 9 exponentbits instead of 8 exponent bits) when storing the single precisionresult value in the 64 bit register. Reducing the bits of mantissaallows the single precision result value to only use 32 bits total eventhough the exponent format is not stored in the 8 exponent bit format ofIEEE 754-2008 for single precision (as shown in FIG. 11).

FIG. 10 illustrates a method 1000 to perform mixed precision estimateexecuted by the circuits 312 according to an embodiment. Note thatalthough the circuits 312 have been identified as performing certainfunctions (e.g., wired with hardware components to execute as discussedherein) for explanatory purposes, the circuits 312 are part of thecircuitry 310 (the hardware forming the processor core). Any discussionof the circuits 312 applies to the circuitry 310, both of which form theprocessor 305 (i.e., the processing circuit).

The circuits 312 receive an input of a first precision having a wideprecision value at block 1005. The input may be a double precision valuein a 64 bit format. The circuits 312 compute an output (for estimateinstructions, such as reciprocal estimate (e.g., for 1/x) and reciprocalsquare root estimate (e.g., 1/√x)) in an output exponent rangecorresponding to a narrow precision value based on the inputcorresponding to the wide precision value at block 1010. The output withthe narrow precision value may be a single precision value in a 32 bitformat.

The circuits 312 store the output in a 64 bit register of the registers315 where the architected register storage format of the register is ina wide precision format (i.e., 64 bit register format).

Based on the wide precision value of the input having an input exponentfailing to correspond to the output exponent range (e.g., failing blocks425, 430, 510, 515, 705, and/or 905), the circuits 312 generate theoutput as an out of range value. The out of range value comprises zeroand/or infinity.

Based on the input comprising a wide not a number (NaN), the circuits312 convert the wide not a number to a narrow not a number in which nota number properties are preserved. In accordance with one embodiment, aNaN value is computed by generating a NaN mantissa consisting of thefirst 23 NaN mantissa bits of a wide input NaN. In one case, the loworder bits are masked and ORed into a single bit position of the resultNaN mantissa, which would otherwise consist of a mantissa consistingonly of zeros. In another embodiment, the result mantissa is set to apre-defined NaN mantissa value when truncation would otherwise yield anall zero mantissa.

Based on the input having the wide precision value with an inputexponent failing to adhere to a valid exponent range of a valid singleprecision value (e.g., the input exponent is greater that 127 but lessthan 149), the circuits 312 generate a mantissa mask based on the inputexponent to be applied to a mantissa of the output (as discussed inblocks 805, 810, 910, and 915). Also, the circuits 312 add an additionalexponent bit beyond eight exponent bits (for the 32 bit register formatof register 605) to account for the input exponent failing to adhere tothe valid exponent range of the valid single precision value, and thecircuits 312 apply the mantissa mask to the mantissa of the output toreduce mantissa bits according to a degree in which the input exponentfails to adhere to the valid exponent range. The circuits 312 store theoutput (number) in a sixty-four bit register with the additionalexponent bit beyond eight exponents bits and with the mantissa of theoutput reduced, such that the output with the additional exponent bitequals to thirty-two bits for single precision while stored by havingthe mantissa reduced (as discussed in Tables 3 and 4). The circuits 312present the output (from the 64 bit register) as the narrow precisionvalue with the eight exponent bits, and the valid exponent rangecorresponds to the eight exponent bits.

Various examples have been applied for computing reciprocal estimatesfor mixed precision, but the disclosure is not meant to be limited. Afourth embodiment discusses mixed precision multiply-estimateinstruction for computing single precision result for double precisioninputs.

Turning to FIG. 11, a block diagram 1100 illustrates an exemplary doubleprecision multiply estimate function 1105 that processes a doubleprecision input for input value 405 and returns a single precisionresult value 450 according to the fourth embodiment. Denormal inputs areflushed to 0.

Estimate instructions of the double precision multiply estimate function1105 avoid rounding and denormalization circuits commonly used forarithmetic operations. An example of multiply estimate is(x^(n))·(y^(m)).

In accordance with the fourth embodiment, no denormal single precisionresults are returned because the exponent 1 plus exponent 2 less than−127 detect 1110 will check for such exponents, and numbers outside thenormalized range are “flushed” to zero when a double precision number isan input for which the result of a multiply estimate cannot berepresented as a normalized single precision number.

The exponent 1 plus exponent 2 greater than 127 detect checks for inputexponents greater than 127, and the circuits 312 set the singleprecision result value 450 to infinity. As discussed herein, when theinput exponent exceeds the range (e.g., if less than −127 or greaterthan 127), a force to predefined value (one of +0, −0, +infinity and−infinity) is performed by the circuits 312.

FIG. 12 illustrates an example of a computer 1200 having capabilities,which may be included in exemplary embodiments. Various methods,procedures, modules, flow diagrams, tools, application, circuits,elements, and techniques discussed herein may also incorporate and/orutilize the capabilities of the computer 1200. Moreover, capabilities ofthe computer 1200 may be utilized to implement features of exemplaryembodiments discussed herein. One or more of the capabilities of thecomputer 1200 may be utilized to implement, to connect to, and/or tosupport any element discussed herein (as understood by one skilled inthe art) in FIGS. 1-11 and 13.

Generally, in terms of hardware architecture, the computer 1200 mayinclude one or more processors 1210, computer readable storage memory1220, and one or more input and/or output (I/O) devices 1270 that arecommunicatively coupled via a local interface (not shown). The localinterface can be, for example but not limited to, one or more buses orother wired or wireless connections, as is known in the art. The localinterface may have additional elements, such as controllers, buffers(caches), drivers, repeaters, and receivers, to enable communications.Further, the local interface may include address, control, and/or dataconnections to enable appropriate communications among theaforementioned components.

The processor 1210 is a hardware device for executing software that canbe stored in the memory 1220. The processor 1210 can be virtually anycustom made or commercially available processor, a central processingunit (CPU), a data signal processor (DSP), or an auxiliary processoramong several processors associated with the computer 1200, and theprocessor 1210 may be a semiconductor based microprocessor (in the formof a microchip) or a macroprocessor.

The computer readable memory 1220 can include any one or combination ofvolatile memory elements (e.g., random access memory (RAM), such asdynamic random access memory (DRAM), static random access memory (SRAM),etc.) and nonvolatile memory elements (e.g., ROM, erasable programmableread only memory (EPROM), electronically erasable programmable read onlymemory (EEPROM), programmable read only memory (PROM), tape, compactdisc read only memory (CD-ROM), disk, diskette, cartridge, cassette orthe like, etc.). Moreover, the memory 1220 may incorporate electronic,magnetic, optical, and/or other types of storage media. Note that thememory 1220 can have a distributed architecture, where variouscomponents are situated remote from one another, but can be accessed bythe processor 1210.

The software in the computer readable memory 1220 may include one ormore separate programs, each of which comprises an ordered listing ofexecutable instructions for implementing logical functions. The softwarein the memory 1220 includes a suitable operating system (O/S) 1250,compiler 1240, source code 1230, and one or more applications 1260 ofthe exemplary embodiments. As illustrated, the application 1260comprises numerous functional components for implementing the features,processes, methods, functions, and operations of the exemplaryembodiments. The application 1260 of the computer 1200 may representnumerous applications, agents, software components, modules, interfaces,controllers, etc., as discussed herein but the application 1260 is notmeant to be a limitation.

The operating system 1250 may control the execution of other computerprograms, and provides scheduling, input-output control, file and datamanagement, memory management, and communication control and relatedservices.

The application(s) 1260 may employ a service-oriented architecture,which may be a collection of services that communicate with each. Also,the service-oriented architecture allows two or more services tocoordinate and/or perform activities (e.g., on behalf of one another).Each interaction between services can be self-contained and looselycoupled, so that each interaction is independent of any otherinteraction.

Further, the application 1260 may be a source program, executableprogram (object code), script, or any other entity comprising a set ofinstructions to be performed. When a source program, then the program isusually translated via a compiler (such as the compiler 1240),assembler, interpreter, or the like, which may or may not be includedwithin the memory 1220, so as to operate properly in connection with theO/S 1250. Furthermore, the application 1260 can be written as (a) anobject oriented programming language, which has classes of data andmethods, or (b) a procedure programming language, which has routines,subroutines, and/or functions.

The I/O devices 1270 may include input devices (or peripherals) such as,for example but not limited to, a mouse, keyboard, scanner, microphone,camera, etc. Furthermore, the I/O devices 1270 may also include outputdevices (or peripherals), for example but not limited to, a printer,display, etc. Finally, the I/O devices 1270 may further include devicesthat communicate both inputs and outputs, for instance but not limitedto, a NIC or modulator/demodulator (for accessing remote devices, otherfiles, devices, systems, or a network), a radio frequency (RF) or othertransceiver, a telephonic interface, a bridge, a router, etc. The I/Odevices 1270 also include components for communicating over variousnetworks, such as the Internet or an intranet. The I/O devices 1270 maybe connected to and/or communicate with the processor 1210 utilizingBluetooth connections and cables (via, e.g., Universal Serial Bus (USB)ports, serial ports, parallel ports, FireWire, HDMI (High-DefinitionMultimedia Interface), etc.).

When the computer 1200 is in operation, the processor 1210 is configuredto execute software stored within the memory 1220, to communicate datato and from the memory 1220, and to generally control operations of thecomputer 1200 pursuant to the software. The application 1260 and the O/S1250 are read, in whole or in part, by the processor 1210, perhapsbuffered within the processor 1210, and then executed.

When the application 1260 is implemented in software it should be notedthat the application 1260 can be stored on virtually any computerreadable storage medium for use by or in connection with any computerrelated system or method. In the context of this document, a computerreadable storage medium may be an electronic, magnetic, optical, orother physical device or means that can contain or store a computerprogram for use by or in connection with a computer related system ormethod.

The application 1260 can be embodied in any computer-readable medium1220 for use by or in connection with an instruction execution system,apparatus, server, or device, such as a computer-based system,processor-containing system, or other system that can fetch theinstructions from the instruction execution system, apparatus, or deviceand execute the instructions. In the context of this document, a“computer-readable storage medium” can be any means that can store,read, write, communicate, or transport the program for use by or inconnection with the instruction execution system, apparatus, or device.The computer readable medium can be, for example but not limited to, anelectronic, magnetic, optical, or semiconductor system, apparatus, ordevice.

More specific examples (a non-exhaustive list) of the computer-readablemedium 1220 would include the following: an electrical connection(electronic) having one or more wires, a portable computer diskette(magnetic or optical), a random access memory (RAM) (electronic), aread-only memory (ROM) (electronic), an erasable programmable read-onlymemory (EPROM, EEPROM, or Flash memory) (electronic), an optical fiber(optical), and a portable compact disc memory (CDROM, CD R/W) (optical).

In exemplary embodiments, where the application 1260 is implemented inhardware, the application 1260 can be implemented with any one or acombination of the following technologies, which are each well known inthe art: a discrete logic circuit(s) having logic gates for implementinglogic functions upon data signals, an application specific integratedcircuit (ASIC) having appropriate combinational logic gates, aprogrammable gate array(s) (PGA), a field programmable gate array(FPGA), etc.

It is understood that the computer 1200 includes non-limiting examplesof software and hardware components that may be included in variousdevices, servers, and systems discussed herein, and it is understoodthat additional software and hardware components may be included in thevarious devices and systems discussed in exemplary embodiments.

As described above, embodiments can be embodied in the form ofcomputer-implemented processes and apparatuses for practicing thoseprocesses. An embodiment may include a computer program product 1300 asdepicted in FIG. 13 on a computer readable/usable medium 1302 withcomputer program code logic 1304 containing instructions embodied intangible media as an article of manufacture. Exemplary articles ofmanufacture for computer readable/usable medium 1302 may include floppydiskettes, CD-ROMs, hard drives, universal serial bus (USB) flashdrives, or any other computer-readable storage medium, wherein, when thecomputer program code logic 1304 is loaded into and executed by acomputer, the computer becomes an apparatus for practicing theinvention. Embodiments include computer program code logic 1304, forexample, whether stored in a storage medium, loaded into and/or executedby a computer, or transmitted over some transmission medium, such asover electrical wiring or cabling, through fiber optics, or viaelectromagnetic radiation, wherein, when the computer program code logic1304 is loaded into and executed by a computer, the computer becomes anapparatus for practicing the invention. When implemented on ageneral-purpose microprocessor, the computer program code logic 1304segments configure the microprocessor to create specific logic circuits.

As will be appreciated by one skilled in the art, aspects of the presentinvention may be embodied as a system, method or computer programproduct. Accordingly, aspects of the present invention may take the formof an entirely hardware embodiment, an entirely software embodiment(including firmware, resident software, micro-code, etc.) or anembodiment combining software and hardware aspects that may allgenerally be referred to herein as a “circuit,” “module” or “system.”Furthermore, aspects of the present invention may take the form of acomputer program product embodied in one or more computer readablemedium(s) having computer readable program code embodied thereon.

Any combination of one or more computer readable medium(s) may beutilized. The computer readable medium may be a computer readable signalmedium or a computer readable storage medium. A computer readablestorage medium may be, for example, but not limited to, an electronic,magnetic, optical, electromagnetic, infrared, or semiconductor system,apparatus, or device, or any suitable combination of the foregoing. Morespecific examples (a non-exhaustive list) of the computer readablestorage medium would include the following: an electrical connectionhaving one or more wires, a portable computer diskette, a hard disk, arandom access memory (RAM), a read-only memory (ROM), an erasableprogrammable read-only memory (EPROM or Flash memory), an optical fiber,a portable compact disc read-only memory (CD-ROM), an optical storagedevice, a magnetic storage device, or any suitable combination of theforegoing. In the context of this document, a computer readable storagemedium may be any tangible medium that can contain, or store a programfor use by or in connection with an instruction execution system,apparatus, or device.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including, but not limited to,electro-magnetic, optical, or any suitable combination thereof. Acomputer readable signal medium may be any computer readable medium thatis not a computer readable storage medium and that can communicate,propagate, or transport a program for use by or in connection with aninstruction execution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmittedusing any appropriate medium, including but not limited to wireless,wireline, optical fiber cable, RF, etc., or any suitable combination ofthe foregoing.

Computer program code for carrying out operations for aspects of thepresent invention may be written in any combination of one or moreprogramming languages, including an object oriented programming languagesuch as Java, Smalltalk, C++ or the like and conventional proceduralprogramming languages, such as the “C” programming language or similarprogramming languages. The program code may execute entirely on theuser's computer, partly on the user's computer, as a stand-alonesoftware package, partly on the user's computer and partly on a remotecomputer or entirely on the remote computer or server. In the latterscenario, the remote computer may be connected to the user's computerthrough any type of network, including a local area network (LAN) or awide area network (WAN), or the connection may be made to an externalcomputer (for example, through the Internet using an Internet ServiceProvider).

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems) and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer program instructions. These computer program instructions maybe provided to a processor of a general purpose computer, specialpurpose computer, or other programmable data processing apparatus toproduce a machine, such that the instructions, which execute via theprocessor of the computer or other programmable data processingapparatus, create means for implementing the functions/acts specified inthe flowchart and/or block diagram block or blocks.

These computer program instructions may also be stored in a computerreadable medium that can direct a computer, other programmable dataprocessing apparatus, or other devices to function in a particularmanner, such that the instructions stored in the computer readablemedium produce an article of manufacture including instructions whichimplement the function/act specified in the flowchart and/or blockdiagram block or blocks.

The computer program instructions may also be loaded onto a computer,other programmable data processing apparatus, or other devices to causea series of operational steps to be performed on the computer, otherprogrammable apparatus or other devices to produce a computerimplemented process such that the instructions which execute on thecomputer or other programmable apparatus provide processes forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof code, which comprises one or more executable instructions forimplementing the specified logical function(s). It should also be notedthat, in some alternative implementations, the functions noted in theblock may occur out of the order noted in the figures. For example, twoblocks shown in succession may, in fact, be executed substantiallyconcurrently, or the blocks may sometimes be executed in the reverseorder, depending upon the functionality involved. It will also be notedthat each block of the block diagrams and/or flowchart illustration, andcombinations of blocks in the block diagrams and/or flowchartillustration, can be implemented by special purpose hardware-basedsystems that perform the specified functions or acts, or combinations ofspecial purpose hardware and computer instructions.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the invention. Asused herein, the singular forms “a”, “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprises”and/or “comprising,” when used in this specification, specify thepresence of stated features, integers, steps, operations, elements,and/or components, but do not preclude the presence or addition of onemore other features, integers, steps, operations, element components,and/or groups thereof.

The corresponding structures, materials, acts, and equivalents of allmeans or step plus function elements in the claims below are intended toinclude any structure, material, or act for performing the function incombination with other claimed elements as specifically claimed. Thedescription of the present invention has been presented for purposes ofillustration and description, but is not intended to be exhaustive orlimited to the invention in the form disclosed. Many modifications andvariations will be apparent to those of ordinary skill in the artwithout departing from the scope and spirit of the invention. Theembodiment was chosen and described in order to best explain theprinciples of the invention and the practical application, and to enableothers of ordinary skill in the art to understand the invention forvarious embodiments with various modifications as are suited to theparticular use contemplated.

The flow diagrams depicted herein are just one example. There may bemany variations to this diagram or the steps (or operations) describedtherein without departing from the spirit of the invention. Forinstance, the steps may be performed in a differing order or steps maybe added, deleted or modified. All of these variations are considered apart of the claimed invention.

While the preferred embodiment to the invention had been described, itwill be understood that those skilled in the art, both now and in thefuture, may make various improvements and enhancements which fall withinthe scope of the claims which follow. These claims should be construedto maintain the proper protection for the invention first described.

What is claimed is:
 1. A computer program product for performing a mixed precision estimate, the computer program product comprising: a non-transitory storage medium readable by a computer having a processing circuit and storing instructions for execution by the computer, wherein the computer comprises a wide precision format register having an architected register storage format in a wide precision format and extra exponent bits compared to a narrow precision format register having an architected register storage format in a narrow precision format, and wherein executing the instructions comprises: receiving, by the processing circuit, a floating-point input of a wide precision having a wide precision value; computing, by the processing circuit, a floating-point output of an estimate operation in an output exponent range corresponding to a narrow precision value based on the input having the wide precision value; generating, by the processing circuit, a mantissa mask from the input exponent based on the input having the wide precision value with an input exponent failing to adhere to a valid exponent range of a valid single precision value; applying, by the processing circuit, the mantissa mask to a mantissa of the floating-point output before storage, wherein the mantissa mask formats the output to take any of the extra exponent bits in the wide precision format register, while relinquishing a corresponding amount of mantissa bits, thereby maintaining the output in the output exponent range corresponding to the narrow precision value; and storing, by the processing circuit, the formatted output having the narrow precision value in the wide precision format register having the architected register storage format in the wide precision format.
 2. The computer program product of claim 1, wherein the method further comprises based on the wide precision value of the input having an input exponent failing to correspond to the output exponent range, generating the output as an out of range value.
 3. The computer program product of claim 2, wherein the out of range value comprises at least one of zero and infinity.
 4. The computer program product of claim 1, wherein the method further comprises based on the input comprising a wide not a number (NaN), converting the wide not a number to a narrow not a number in which not a number properties are preserved.
 5. The computer program product of claim 1, wherein the method further comprises adding an additional exponent bit beyond eight exponent bits to account for the input exponent failing to adhere to the valid exponent range of the valid single precision value; and applying the mantissa mask to the mantissa of the output to reduce mantissa bits according to a degree in which the input exponent fails to adhere to the valid exponent range.
 6. The computer program product of claim 5, wherein the method further comprises storing the output in a sixty-four bit register with the additional exponent bit beyond the eight exponent bits and with the mantissa of the output reduced; wherein the output with the additional exponent bit equals to thirty-two bits for single precision while stored by having the mantissa reduced; wherein the processing circuit is configured to present the output as the narrow precision value with the eight exponent bits; and wherein the valid exponent range corresponds to the eight exponent bits.
 7. A method for performing a mixed precision estimate, which avoids a need for a normalization and denormalization circuit, the method comprising: receiving, by a processing circuit, a floating-point input of a wide precision having a wide precision value; computing, by the processing circuit, a floating-point output of an estimate operation in an output exponent range corresponding to a narrow precision value based on the input having the wide precision value; based on the input having the wide precision value with an input exponent failing to adhere to a valid exponent range of a valid single precision value, generating a mantissa mask based on the input exponent to be applied to a mantissa of the output; generating, by the processing circuit, a formatted output by adding an additional exponent bit beyond eight exponent bits to account for the input exponent failing to adhere to the valid exponent range of the valid single precision value, and applying the mantissa mask to the mantissa of the output to reduce mantissa bits according to a degree in which the input exponent fails to adhere to the valid exponent range: and storing, by the processing circuit, the formatted output having the narrow precision value in a wide precision format register having an architected register storage format in a wide precision format, wherein the wide precision format register includes extra exponent bits compared to a narrow precision format register having an architected register storage format in a narrow precision format for storing the additional exponent bit.
 8. The method of claim 7, further comprising based on the wide precision value of the input having an input exponent failing to correspond to the output exponent range, generating the output as an out of range value.
 9. The method of claim 8, wherein the out of range value comprises at least one of zero and infinity. 